Robust and low complexity Bayesian data fusion for hybrid cooperative vehicular localization
| Auteurs | Hoang G.M., Denis B., Harri J., Slock D.T.M. |
| Year | 2017-0366 |
| Source-Title | IEEE International Conference on Communications |
| Affiliations | CEA-Leti, MINATEC Campus, 17 avenue des Martyrs, Grenoble, France, EURECOM, SophiaTech Campus, 450 route des Chappes, Biot, France |
| Abstract | This paper addresses Particle Filter (PF)-based hybrid Cooperative Localization (CLoc) strategies consisting of fusing absolute position information from embedded Global Navigation Satellite System (GNSS) with relative distance-dependent estimates using Impulse Radio - Ultra WideBand (IR-UWB) technology. Such hybrid GNSS/IR-UWB CLoc yet cannot benefit from the high precision estimates from the IR-UWB due to the disparity between GNSS position and IR-UWB V2V ranging noises, leading to a divergence in CLoc accuracy. This paper first investigates the source of such counter-intuitive effect, and second proposes a novel adaptive Bayesian dithering technique to improve the efficiency of GNSS/IR-UWB fusion-based CLoc. This strategy increases the probability to reach a 20 cm accuracy from 50% (conventional IR-UWB and WiFi PF) to 90%. © 2017 IEEE. |
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| ISSN | 15503607 |
| Lien vers article | Link |